Job Description:

The Role

Quantitative Research and Investments (QRI) Data Operations is seeking a highly motivated data operations analyst to create and maintain data quality rules, investigate potential data quality issues, and work with both internal partners and external providers to remedy data issues to ensure all information required for the investment management process including holdings, security reference data, end of day pricing, compliance, and a wide range of vendor data are delivered consistently, accurately and on a timely basis, and supported.

This role is an opportunity for a motivated individual with a combination of strong market data experience, analytical skills and an attention to detail, to develop meaningful data domain expertise central to the quantitative investment process and address sophisticated data problems in a fast-paced environment that have a significant impact on both our research and customers' portfolios.

• Enable QRI's access to clean, timely and relevant data, working closely with key technology and business partners for high quality data
• Independently respond to data quality issues in overnight feeds, enabling fast and consistent responses to upstream issues and insulating production and research from them
• Partner on the stewardship of data assets used in research and quantitative models
• Support the data onboarding effort, including receiving new datasets and associated DQ systems from the Data Engineering team and reviewing the standards and to certify historical data and build knowledge of the dataset
• Analyze systems and processes to find efficiencies and improve accuracy and timeliness of reporting

• Prior experience with vendor-provided data, including FactSet, Bloomberg, IBES estimates, Compustat and/or Worldscope fundamental data, Morningstar, MSCI, Thomson Reuters, IDC, Markit, FTSE Russell
• Experience with market risk data vendors, including BARRA, Axioma, Northfield, and Bloomberg's PORT
• Experience in security, company, portfolio, and index-level information used across the financial industry
• Highly analytical able to comprehend large data sets, develop and implement the right quality controls for these datasets
• Highly proactive and self-motivated with the ability to meet objectives independently, with shown attention to detail and high-level goals
• Experience in SQL, Python, Snowflake and / or Oracle and related tools.
• 2+ years' experience in data operations and/or support teams delivering value to the team and organization
• Bachelor's degree (or higher) in finance or other quantitative or research-related field
• Exposure to methods, tools and metrics for autonomous and discretionary anomaly detection, and data quality workflow is a plus
• Excellent written and verbal skills; experience working with both technical and investment teams
• Consistent record of working with sophisticated data environments and associated technology and analytics infrastructure needed to support these environments
• Perform root-cause analysis in complex environments and work with other global operational teams and external data providers to correct issues identified
• Familiarity with creating automated processes to identify errors to ensure high quality of data to support the investment process
• Experience in detailing key procedures and calculations, and validating data
• Investment Management business domain expertise across some combination of research, portfolio management, trading and investment operations